B O Bebe

Abstract

Smallholder dairy intensification in the Kenya
highlands is characterised by a shift from free- to semi-zero- or zero-grazing
management in response to inter-generational division of landholdings, keeping
of smaller herds of dairy breeds, dependency on external feed resources and poor
reproductive performance. As other sources of breeding stock are limited, the
changes in herd structure and demographic rates in smallholder herds raise
concerns as to whether these herds can produce sufficient replacement stock
needed to sustain the continuing intensification. A deterministic model was
developed to assess the potential for smallholder herds to be self-sustaining
and to generate surplus replacement stock for aspiring dairy farmers as
management continues to shift from free- to zero-grazing. The base situation
reflected the actual proportion of free, semi-zero- and zero-grazing farms and
the size, structure and demographic rates of the herds in representative low-,
medium- and high- intensive farming systems in the Kenya highlands.

Model estimates at the base situation showed
that the replacement stock available in all the three systems were sufficient
for maintaining the breeding population with a surplus remaining for aspiring
farmers adopting/or shifting from free- to semi-zero- or zero-grazing. However,
the number of replacement stock available decreased with the reduction in farms
practising free-grazing, because semi-zero- and zero-grazing farms are unable to
produce their own replacement stock. A 4% annual decrease in the proportion of
free-grazing farms resulted in insufficient replacement stock to maintain the
existing herds in high- but not in low- and medium- intensive systems. In
free-grazing farms, reducing the rate of cow mortalities and the proportion of
replacement stock sold during the rearing period were the most promising
interventions to sufficiently produce the needed replacement stock. Prospects
for the continued intensification of smallholder dairying in the Kenya highlands
thus depend upon the proportion of free-grazing farms maintained within the
farming systems. A rational policy would be to promote intensification of
smallholder dairying within a stratified dairy sub-sector.

Introduction

Insufficient supply of dairy heifers is a major constraint to
the development of smallholder dairy production in many developing countries (De
Jong 1996; Afifi-Affat 1998). In Kenya where the integration of dairying into
smallholder farming has been relatively successful, public owned large-scale
farms used to produce replacement heifers for smallholders at subsidised prices.
However, a large majority of large-scale dairy farms including those privately
owned have collapsed or have been subdivided for resettlement of smallholders,
particularly in the highland areas where dairying is concentrated (Bebe et al
2002).

With human population densities continuing to rise and
landholdings to shrink in the Kenya highlands, the trend amongst smallholders is
to intensify their dairying from free- to semi-zero- and zero-grazing (stall
feeding). This intensification is characterised by keeping smaller herds of
dairy breeds often without heifers, dependency on external feed resources and
poor reproductive performance (Bebe et al 2002). A recent study of the dynamics
of smallholder herds in the Kenya highlands showed that semi-zero- and
zero-grazing farms, which comprise over three quarters of all the farms, are
unable (or unwilling) to produce the heifers needed to maintain their herd size,
whereas free-grazing farms produce surplus heifers (Bebe et al 2003a).
Smallholders source heifers mainly from fellow smallholders within their local
farming systems and less frequently from outside their farming systems or from
large-scale farms because of high pricing and fear of poor adaptability. The
trend of shifting from free- to semi-zero- or zero-grazing may result in the
need for externally produced dairy heifers for replacement and raises concern
about the prospects for maintaining and expanding smallholder dairying in the
Kenya highlands.

Deterministic herd models have been used to explore the
potential for producing the heifers needed to sustain current herd populations
and a surplus for sale to other farmers (Shaw and Hoste 1987; Houterman et al
1993; Affi-Affat 1998). These models projected heifer generation only on the
basis of reproductive and survival rates in the herds, ignoring the dynamics in
the farming systems. Smallholder farming systems are dynamic, and as exemplified
in the Kenya highlands (Bebe et al 2002), they evolve with changes in population
growth, land use, economic conditions and development policies. A deterministic
model was thus developed to assess whether there is the potential in smallholder
farming systems of having herds that are both self-sustaining and generate
surplus heifers for aspiring dairy farmers within systems intensifying from
free- to zero-grazing dairying.

Materials and methods

Farming
systems

Three smallholder farming systems in the Kenya highlands
representing low-, medium- and high- intensive dairy farming systems have been
described by Bebe et al (2002). Table 1 gives the household population, their
dairying management practices, herd size and structure. The land use patterns,
population densities and farm sizes, market access, and the proportion of dairy
farms practising free-, semi-zero- and zero-grazing within a farming area
defined the farming systems. Smallholder farming households in Olkalou division
of Nyandarua district, Rongai division of Nakuru district and Limuru division of
Kiambu district respectively represented the low-, medium- and high- intensive
farming systems.

Table 1. Distinguishing
characteristics of low, medium and high intensive farming systems in
the Kenya highlands

Characteristics

Farming system

Low intensive

Medium intensive

High intensive

Agro-ecological
potential

High

Medium

High

Market access

Low

Medium

High

Population density,
people/km2

206

288

583

Farm size, ha

5.4

2.0

1.1

Stocking rate, TLU/ha

1.2

1.7

2.6

Milk production,
litres/ha/day

0.65

0.79

1.58

Proportion of milk
consumed by household, %

41

29

30

Purchased feeds, US
$/year

62

188

217

Returns to land from
dairy, US $/ha

334

343

555

aHouseholds,
n

6030

11330

14520

Households with cattle
currently, %

85

58

71

Households currently
practising:

Free-grazing, %

23

32

27

Semi-zero-grazing, %

72

49

8

Zero-grazing, %

5

19

65

Households that 10 years
ago practised:

Free-grazing, %

27

53

37

Semi-zero-grazing, %

67

30

25

Zero-grazing, %

6

17

38

Source: (i) Bebe et
al 2002.

(ii) aCBS
2000.

The low intensive farming systems are
found in areas of high agro-ecological potential for cropping and dairying (Jaetzold
and Schmidt 1983), but with low market access. Market access was defined on the
basis of human population density, local demand for milk, types of roads and the
availability of milk marketing institutions (Staal et al 2001). The high
intensive farming systems are found in areas of high agro-ecological potential
with better market access. Medium intensive systems are in the medium
agro-ecological potential areas with medium market access. Proportionately,
there are more zero-grazing farms in high- than in low- intensive farming
systems in which human population densities
are lower. Consequently, on average farm and herd sizes are smaller but
cattle stocking rates are higher with the shift from low to high intensive
farming systems. As average herd size decreases cows generally form a larger
part of the herd, which has fewer or no heifers for replacement. A
characteristic pattern of management with the shift from low to high intensive
farming systems is increased use of purchased feeds (Bebe et al 2002).

Model design

A dynamic deterministic model was developed to estimate on an
annual basis the production of dairy heifers needed to maintain the herd
population and surplus heifers for aspiring farmers in the representative low-,
medium- and high- intensive farming systems when smallholder farms shift from
free- to semi-zero- or zero-grazing dairying. The schematic representation of
the model is given in Figure 1 and it is operated in Microsoft Excel ®.

Figure 1.
Schematic representation of the herd model used to project the potential
production of dairy heifers in the low-,
medium- and high- intensive smallholder
farming systems in the Kenya highlands

Household input data are the total number of households and
the proportions of those practising free-, semi-zero- or zero-grazing in each
farming system. Herd input data are the size, structure and annual demographic
rates of the herds for free-, semi-zero- or zero-grazing farms. The input values
used for the base situation reflect smallholder dairying in the Kenya highlands
(C.B.S. 2000; Staal et al 2001; Bebe et al 2003a).

The simulation of the herd dynamics uses a matrix recurrence
equation according to Caswell (1989) and Lesnoff (1999). The simulation is run
for a period of ten years and is performed separately for each farming system.
The availability of dairy heifers needed to maintain the herd population in each
farming system and any surplus heifers available for aspiring farmers is
calculated on an annual basis using the information on household numbers and
their type of dairying with the associated herd size and structure and
demographic rates. The model calculates the initial herd population from the
number of households with cattle given the size and structure of the herds.
The herd projections use the demographic rates overtime and assume that
population growth only depends on demographic rates of females.
A herd comprises one class of heifer-calves
(pre-weaned females), two classes of heifers (post-weaned females below one year
and above one year until first calving) and eleven classes of cows (3 to >12
years of age)to reflect the observed
herd structures (Staal et al 2001). Of the heifers and cows purchased, 90%
originate from within the farming system and the other 10% from outside the
farming system (Bebe et al 2003a), linkage with medium- and large-scale farms is
thus assumed insignificant.

Herd projections

The distribution of individual female animals over age groups
in year t is given by a vector,

(t) = [n1(t),…..,
n14(t)]

where n1(t),…..,n14(t) are the number
of females in age group 1 to 14 in year t.

This vector is linked from one year to the next by an
age-transition matrix that contains the maximum likelihood estimates of annual
birth rates and the survival rates for each animal class in projecting the
population changes from year t to t+1. This population projection matrix A
writes as:

n (t + 1) = An (t)
(1).

Survival from year t to t + 1 writes
as Pi+1
= 1 - m – s + b

based on Lesnoff (1999), where m is mortality rate, s is
selling rate and b is buying rate associated with each animal class in free-,
semi-zero- or zero-grazing farms. Demographic rates apply to the population at
the beginning of the year.

Replacements to maintain herd size and to supply a surplus
for aspiring dairy farmers

The number of dairy heifers produced annually is calculated
as females surviving to age at first breeding. This number is expressed as dairy
heifers available per cow leaving the herd, which includes all deaths and sales.
The productive life of a cow is defined by the probability of disposal (death
and sales: Table 2); for instance, a disposal probability of 0.26 in
zero-grazing farms translates (reciprocal) to a productive life of 3.8 years.
Thus, the number of dairy heifers per cow leaving the herd has to be equal or
greater than one (1) if the herd size is to be at least maintained on an annual
basis. When it is below one (1), it implies
that dairy heifers for replacement outside the farming system have to be bought
to maintain or expand the herd size. Any available dairy heifers above the
numbers needed to replace cows leaving the herd for purposes of maintaining the
population is surplus. These surplus heifers are available for potential adopter
farmers. These are non-cattle-keeping households or those presently owning
free-grazing farms who are more likely to adopt/or shift to semi-zero- or
zero-grazing because their holdings become smaller due to subdivision and
fragmentation through family inheritance. The number of dairy heifers per
adopter farmer has to be above or equal to one (1) for surplus dairy heifers to
be available for the potential adopter dairy farmers.

Sensitivity analyses

Sensitivity analyses evaluated the effect of the decrease in
the proportion of free-grazing farms and the changes in herd demographic
parameters on the number of dairy heifers available for replacing cows leaving
the herd and a surplus for farmers potentially adopting/or shifting to
semi-zero- or zero-grazing. Relative to the base situation, the proportion of
households annually shifting from free- to semi-zero- or zero-grazing was set to
vary from 1 to 5 percentage units to reflect the ongoing shift from free- to
semi-zero- or zero-grazing (Table 1) observed in these farming systems (Bebe et
al2002). The decrease in the proportion of free-grazing farms results in
an increase in the number of semi-zero- and zero-grazing farms, and the
probability of a farmer shifting from free- to semi-zero- or to zero-grazing
dairying is assumed to have an equal probability because a farmer may adopt
either of these.

An annual change of ±3
percentage units relative to the base situation in calving rates, heifer-calf
mortality rates, cow mortality rates and proportion of dairy heifers sold during
the rearing period, were made in free-, semi-zero- or zero-grazing farms in each
of the farming systems. This was to reflect feasible interventions on the basis
of experiences with smallholder dairying systems reported in literature. Animal
health interventions in intensive smallholder herds in Kagera region of Tanzania
reduced overall cattle mortality rate from 11.5 to 7% over a period of nine
years (De Jong 1996). The introduction of improved calf-rearing packages for
smallholders in Bahati area in the Kenya highlands reduced annual calf mortality
rate by 6 percentage units (Lanyasunya et al 1999).

Results

Base situation

The projected number of dairy heifers produced per cow leaving the herd annually
in free-, semi-zero- and zero-grazing farms at the base situation was
respectively 1.38, 0.89 and 0.78. These rates imply that for the purposes of
maintaining the existing breeding herd population on annual basis, free-grazing
farms produced surplus heifers whereas semi-zero- and zero-grazing farms
produced insufficient heifers. When farms were aggregated at the farming systems
level, there was an annual surplus of 7.7, 11.3 and 3.9% heifers in the low-,
medium- and high- intensive farming systems, respectively (Figure 2).

Figure 2.
Effect of decrease in proportion of free-grazing farms on (a) available surplus
heifers and on (b) potential dairy adopter farmers (%/y) obtaining at least a
heifer in low-, medium-and high- intensive farming systems in the Kenya
highlands

The surplus heifers produced in free-grazing farms were sufficient to offset the
deficits in semi-zero- and zero-grazing farms, with a surplus remaining. In the
high-, medium- and low- intensive farming systems respectively, surplus heifers
were sufficient for 1.6, 2.9 and 4.8% of potential farmers aspiring to adopt/or
shift to semi-zero- or zero-grazing on annual basis for a ten-year period
(Figure 2). Although more surplus heifers were available in the medium- than in
the low- intensive farming systems, potential adopter farmers were more (42 vs
15%: Table 1), hence the lower proportion of farmers obtaining at least one
dairy heifer.

Effect of decrease in the proportion of free-grazing farms
in the farming system

The number of surplus heifers reduced with the decrease in
the proportion of free-grazing farms, consequently lowering the proportion of
farmers obtaining at least a dairy heifer when aspiring to adopt/or shift to
semi-zero- or zero-grazing dairy management (Figure 2). Relative to the base
situation, an annual decrease of 4 percentage units in the proportion of
free-grazing farms produced insufficient heifers for maintaining the existing
breeding herd population in the high intensive system, but not in the low- and
medium- intensive systems. With a 3 percentage unit annual decrease in the
proportion of free-grazing farms, the proportion of potential dairy adopter
farmers obtaining at least a heifer were respectively 0.3, 2.2 and 3.3% in the
high-, medium- and low- intensive farming systems. Through sensitivity analysis
it was estimated that the minimum proportion of free-grazing farms needed to
maintain self-replacing herds was respectively 18, 15 and 12% in the high-,
medium- and low- intensive farming systems.

Effect of changes in the demographic rates

Figure 3 shows the percentage change relative to the base
situation in the number of surplus heifers resulting from a ±3
percentage unit change in the demographic rates made in free-, semi-zero- and
free-grazing farms in the low-, medium- and high- intensive farming systems. The
change in the number of surplus dairy heifers was consistently higher for
changes made in free- than in semi-zero- or zero-grazing farms.

Figure 3.
Percentage (%) change relative to base situation in the number of surplus
heifers resulting from a ±3
percentage unit change in demographic rates made in free-, semi-zero- and
free-grazing farms in low-, medium- and high- intensive farming systems

Thus interventions made in free-grazing farms were the most
promising. A decrease in cow mortality followed by a decrease in the proportion
of heifers sold during the rearing period had the greatest percentage effect on
the number of surplus dairy heifers produced.

Table 3 shows the effect of a ±3
percentage unit change to improve calving rate, reduced heifer selling rate and
reduced cow mortality in free-grazing farms on potential dairy adopter farmers
(%/y) obtaining at least a dairy heifer in low, medium and high intensive
farming systems. Of the potential dairy adopter farmers, those obtaining at
least a dairy heifer were highest with the decrease in cow mortality rate
followed by a decrease in heifer selling rate.

Discussion

Dairy production by smallholder farmers is a means to achieve multiple
objectives: improved food security, supporting crop production, building capital
assets and generating cash income. Smallholder farmers in the Kenya highlands
pursue dairying intensification to maximise the returns from their limited land
and capital. Development agencies encourage intensification of dairying as a
sustainable pathway out of poverty for smallholders (MoA 1998; Delgado et al
2001). An important question is whether smallholder herds have the capacity to
produce their own replacement heifers in numbers sufficient to maintain the
breeding population and to generate surplus heifers for other aspiring dairy
farmers.

Projections over time from deterministic models can be a useful basis for
exploring the dynamics of livestock populations in different farming systems and
with different interventions for development planning or for productivity
assessment (Upton 1989; Wakhungu and Baptist 1992; Lesnoff 1999). This study
applied a deterministic model with input values reflecting the prevailing herd
reproductive performances and the dynamics of smallholder farming systems in the
Kenya highlands. The model results suggested that the potential for maintaining
the current dairy herd and its continued expansion will be dependent upon the
proportion of free-grazing farms maintained in the farming system. With the
stratification within the smallholder dairy systems, the surplus heifers
produced in free-grazing farms serve as foundation stock for new farmers or as
replacement animals for the existing semi-zero- and zero-grazing farms in these
farming systems. The valuable complementarity amongst these farming systems
provides a market in the semi-zero- and zero-grazing farms for the surplus
heifers produced from the free-grazing farms.

With the pressure on land from the continually rising human
and cattle populations, the proportion of households practising free-grazing is
projected to reduce and with it an increased shortage of internally produced
dairy heifers in these farming systems. Consequently, unless alternative
supplies become available, the cost of heifer replacements would rise and fewer
farmers would be able to afford a dairy heifer for replacement, foundation stock
or to expand an existing herd. Insufficient availability of heifers would be
particularly marked in the high intensive farming systems where the proportion
of households practising zero-grazing is already about two-thirds of all the
dairy households (Table 1).

Of the interventions tested for increasing the number of
dairy heifers the most promising was in the free-grazing farms through a
decrease in cow mortality; followed by a reduction in the same system of the
proportion of heifers sold during the rearing period. In the semi-zero- and
zero-grazing farms the low impacts of decreased cow mortality and proportion of
heifers sold is a consequence of a general high animal turnover in all age
classes. To increase the production of dairy heifers in semi-zero- and
zero-grazing farms requires a concomitantly improved calving rate and decreased
voluntary exit of potential replacement heifers. This may be difficult for
households without improved access to affordable credit given that 60 to 85% of
the voluntary exits of female animals are for meeting immediate cash needs of
the household (Bebe et al 2003a).

The major causes of cattle mortality on smallholder farms in
the Kenya highlands are tick-borne diseases and parasitic worm infestations and
their interactions with inadequate quantity and quality of feeding (Gitau et al
1997). Despite the adoption of tick control practices by smallholders, losses
attributable to tick-borne diseases remain high, regardless of level of
intensification in the system (Bebe et al 2003a). Animal health practices, such
as acaricide application, are implemented inconsistently because of limited cash
flow (Batz et al 1999). Interventions to lower cow mortality rates will require
that smallholders have improved access to animal feeds and health services and
adequate incentives to adopt these practices and technologies.

Compared to herds on free-grazing farms, those on semi-zero-
and zero-grazing farms have lower calving rates and higher voluntary exits of
cows and heifers (Table 2) such that a decrease in cow mortality rate alone only
marginally improved the number of heifers available for replacement or herd
expansion in these farming systems. The high proportions of voluntary exits of
heifers are likely the result of decisions by smallholders to reduce competition
for the limited feed resources in order to target feeds to cows for milk
production (Bebe et al 2003b). On average, free-grazing farms are larger in area
and their animals graze on the farmers' own land or on communal lands. Some
farms keep a bull for mating. In contrast semi-zero or zero-grazing farms are
generally smaller in area, they maintain smaller herds with a higher proportion
of cows, which they feed partly on purchased fodder and concentrates.

In a study of herd dynamics of the same population, Bebe et
al (2003a) showed that smallholders buy most (90%) of their replacements from
fellow smallholders within the farming system. Cattle movements between
large-scale and smallholder farms and also between the farming systems are
presently minimal. Consequently smallholders practising semi-zero- and
zero-grazing face problems of obtaining a dairy heifer of the desired genotype
and quality at the required time and at an acceptable price. It is difficult for
these smallholders to rear their own heifers because this requires investment in
feed, veterinary services, housing and labour while income is only generated
later when the animal is sold or is lactating (Mourits et al 1999).

Subsidised heifer-rearing schemes and heifer-in-trust
projects to support smallholders in the rearing of dairy heifers have generally
proved to be unsustainable for farmers and for projects. Experiences with
smallholders in Tanzania and Sri Lanka, for instance, showed that smallholders
did not continue with the recommended management practices beyond the period of
project support (De Jong 1996; Afifi-Affat 1998). These experiences suggest the
need for increased facilities or incentives to access dairy breeding stock from
outside the farming system and to reduce the reproductive wastage as more
households shift from free- to semi-zero- or zero-grazing dairying.Such facilities or incentives in the
form of improved rural infrastructure including water supply need be extended to
semi-arid areas to support dairy production in those areas to ease pressure on
the medium and high potential agro-ecological zones. In that way,
intensification of smallholder dairying can be supported through greater
complementarities between the small- and large-scale components of the dairy
sub-sector, particularly in the supply of dairy heifers.

Conclusions and implications

For smallholder farming systems in the Kenya highlands, the
supply of dairy heifers partially depends upon the proportion of free-grazing
farms maintained in the system and the stratification within the farming
systems. Decreases in the proportion of free-grazing farms leads to a scarcity
of heifers, implying that adoption of dairy production by smallholders is likely
to decrease in areas of high intensive farming systems where two-thirds of the
farms already practice zero-grazing. In the low and medium intensive farming
systems the adoption of dairying can continue at the present rates.

These farming systems respectively corresponded to areas of
low and medium market access, and will need improved marketing infrastructures
and institutional policies to support marketed dairy production. A rational
policy is therefore to promote intensification of smallholder dairying with
greater complementarities between the small- and large-scale components of the
dairy sub-sector.

Acknowledgements

The authors acknowledge support for this study from The
Netherlands Foundation for the Advancement of Tropical Research-WOTRO, the
Smallholder Dairy (R and D) Project (SDP) of the Kenya Ministry of Agriculture and
Rural Development, the Kenya Agricultural Research Institute (KARI) and the
International Livestock Research Institute (ILRI), and the UK Department for
International Development (DFID).

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